library(ever)
library(dplyr)
library(DT)Signals Duplicates Analysis
Quality Control Report for Live Signal Data
Overview
This document analyzes duplicate signals in the live data to identify potential data quality issues and ensure signal integrity across different plates and targets.
Setup
Loading required libraries for data validation and visualization:
Data Validation
Running validation checks on live signals to identify duplicates:
# Validate live signals and identify duplicates
dupes <- validate_live_signals()
# Display summary statistics
cat("Total duplicate records found:", nrow(dupes), "\n")Total duplicate records found: 11200
if (nrow(dupes) > 0) {
cat("Unique targets affected:", length(unique(dupes$`Target Name`)), "\n")
cat("Unique plates affected:", length(unique(dupes$`Plate Barcode`)), "\n")
}Unique targets affected: 1
Unique plates affected: 13
Detailed Duplicate Records
Complete view of all duplicate records with full details:
if (nrow(dupes) > 0) {
datatable(dupes,
caption = "All Duplicate Signal Records",
options = list(
pageLength = 10,
scrollX = TRUE,
dom = 'Blfrtip'
),
filter = 'top') %>%
formatStyle(columns = colnames(dupes), fontSize = '12px')
} else {
cat("No duplicate records found.")
}Warning in instance$preRenderHook(instance): It seems your data is too big for
client-side DataTables. You may consider server-side processing:
https://rstudio.github.io/DT/server.html
Summary by Target and Plate
Consolidated view showing unique combinations of targets, plates, and data types affected by duplicates:
if (nrow(dupes) > 0) {
summary_data <- dupes %>%
select(`Target Name`, `Plate Barcode`, datatype) %>%
distinct() %>%
arrange(`Target Name`, `Plate Barcode`)
datatable(summary_data,
caption = "Unique Target-Plate-Datatype Combinations with Duplicates",
options = list(
pageLength = 15,
scrollX = TRUE,
dom = 'Blfrtip'
),
filter = 'top') %>%
formatStyle(columns = colnames(summary_data), fontSize = '12px')
} else {
cat("No duplicate combinations found.")
}Report generated on 2025-09-25 15:44:21.662523 using the ever package validation functions.